Using Digital Resources for Motivation and Engagementin Learning Mathematics: Reflections from Teachersand Students

Theodore Chao1 & Jason Chen2 & Jon R. Star3 &Chris Dede4

Published online: 13 September 2016# Springer International Publishing 2016

Abstract Students motivation to learn mathematics often declines during the middlegrades. How do we keep students engaged with learning mathematics as it gets morecomplex? One way is through the use of technology, such as computer games,interactive lessons, or on-line videos. Yet evidence from creating technology-basedtasks and resources to motivate students to learn mathematics is mixed, partiallybecause most interventions only loosely incorporate motivational constructs. Thisarticle is part of a larger research project examining the impact of three digital resourceson students motivation and learning in mathematics. In it, we provided resourcestightly aligned to motivational constructs from research: self-efficacy, implicit theoriesof ability, and interest and enjoyment. Students then engaged with these resourcesbefore and after a 2-day mathematical patterns lesson. We present results from inter-views and observations with eighty-eight fifth- to eighth-grade students and their tenteachers. Findings suggest that, even with a minimal encounter over 1 or 2 days,students were able to notice the motivational constructs present within these digitalresources.

Success in mathematics during the middle-school years (typically, ages 11 to 15 in theUSA) is widely recognized as a gatekeeper of later academic and social success (Adelman2006;Moses andCobb 2001). During this period, student motivation to learnmathematicssignificantly declines (Archambault et al. 2010; Blackwell et al. 2007; Dweck 2007;Eccles-Parsons et al. 1983). According to the U.S. National Mathematics Advisory Panelreport, 62 % of the Algebra I teachers surveyed rated working with unmotivated studentsas the single most challenging aspect of teaching (Hoffer et al. 2007).

One approach to this problem of low student motivation is to use technology-basedresources both to spark students interest in learning mathematics and to develop greaterconfidence in mathematical problem solving. Historically, many teachers use technologyin their mathematics classes in a variety of ways, ranging in complexity and cost fromrepurposing commercially available television programs to utilizing computer games.

Even as many teachers embrace technology in their classrooms, the evidencesurrounding the effectiveness of using it to ignite student interest in the academiccontent is sparse (Chen et al. 2016; Chen et al. 2014; Moos and Marroquin 2010). Onereason for this lack of knowledge is because technology is not often aligned withspecific aspects of motivation and content. Rather, the technology is incorrectlyassumed to be generally and comprehensively motivating the presumption thatchildren will be interested in learning or become more confident mathematically simplybecause of the presence of technology.

A second reason for these uncertain results is that much of the research on technology-based resources and tasks explores motivation as an afterthought rather than a central partof the design process. Both these reasons are likely due to a lack of alignment betweentheoretical grounding in well-studied motivation constructs and educational technologydesign (Chen et al. 2012; Moos and Marroquin 2010). As a result, educators andeducational technology designers lack empirical evidence for which types of motivationalconstructs, exemplified in technology design, are useful for whom and under what types ofconditions in order to enhance the learning of mathematics.

We sought to address this evidence gap by exploring how students described theirexperiences when working with three different kinds of digital resources an immersivevideo game, an interactive website, and a commercially produced video chosenspecifically in relation to three distinct frameworks of motivation and engagement. Toexplore their impact on student motivation to learn mathematics, we present a qualitativeanalysis of the views of eighty-eight students (in grades five to eight) and their ten teachersas they participated in a week-long motivational technology intervention, during whichstudents and teachers discussed both the specific resource they had worked with and theirmotivation for learning mathematics. Because the investigation was so short, we focusedon the impact of the intervention on student motivation for learning mathematics, ratherthan trying to measure changes in mathematics content knowledge.

When we say motivation, we specifically mean students interest in mathematics andtheir confidence in relation to success in mathematics (i.e., self-efficacy, implicit theoriesof ability, and interest and enjoyment). Two research questions guided our investigation.

(1) From the standpoint of motivation and engagement, what were studentsperceptions of and experiences with the digital resources?(2) How did teachers of mathematics perceive their students self-efficacy, theirimplicit theories of ability, and their interest and enjoyment in learning mathematics?

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Background Theoretical Framework

Understanding this study requires exploring the theoretical underpinnings that went into thework with each resource. In the sub-sections below, we discuss the theories of motivationinforming the chosen resources. We also examine the research on how each digital elementrelates to a specific motivational construct for learning: self-efficacy, implicit theories ofability, and interest and enjoyment. (See Table 1 for how each resource incorporated aspecific motivational construct and aspect of mathematics learning.)

Self-Efficacy and Mathematics Learning

Mathematics is considered one of the most difficult subjects to master in school(Dweck 2000; NRC 2001). A robust belief in ones capabilities to succeed (i.e. self-efficacy) in mathematics is critical to learning mathematics. More generally, fourdecades of research have shown the importance of self-efficacy to outcomes such aspersistence and perseverance in the face of difficulties, academic achievement, andstudents choice of college majors and careers (Bandura 1997; Brown and Lent 2006;for a review, see Pajares and Urdan 2006).

Given these important outcomes tied to mathematics learning, researchers have ex-plored factors that support self-efficacy. Bandura (1997) posited that self-efficacy isformed by peoples interpretation of four main sources, two of which we target here.First, mastery experiences (the interpretations of ones past accomplishments) constitutethe most powerful source of self-efficacy. Students who interpret their past mathematicsexperiences as successful aremore likely to approach futuremathematics endeavors with astrong belief in their ability to succeed. Second, observing others succeed or fail influencesself-efficacy. Such vicarious experiences are especially influential when observers per-ceive others as being similar to themselves, which is particularly influential when indi-viduals have little experience with the task or are uncertain about the standards by whichthey will be judged. For example, students who have never faced algebra before, or areuncertain about how they will be graded, might turn to siblings, friends, or narratives ofothers with whom they relate to as pertinent informants.

Implicit Theory of Ability in Mathematics

A related belief about competence involves students perceptions about the nature oftheir mathematics abilities, their implicit theory of ability in mathematics. Dweck and

The game: A virtual environment Self-efficacy through vicariousand mastery experiences

Yes

Brainology: A web-based curriculum module Implicit theory of ability No

The video: an off-the-shelf PBS NOVA episode Interest and enjoyment No

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Leggett (1988) posited that individuals typically fall into one of two categories: fixedmindset or incremental/growth mindset. Students holding a fixed mindset believe that,no matter what the circumstances are, ones intellectual abilities are set in stone there is little that can be done about ones smarts (Blackwell et al. 2007; Cury et al.2006; Good et al. 2012; Grant and Dweck 2003). Students holding a fixed mindseteither pursue a task to demonstrate their competence or avoid one for fear of lookingincompetent. These students are more likely to see effort as bad and, in the face ofobstacles, tend to give up prematurely and achieve only at low levels.

On the other hand, students with an incremental or growth mindset believe that,with hard work and appropriate strategies, they can increase their intellectualabilities (Dweck and Leggett 1988). Students holding an incremental mindsetpursue a task or explore a situation simply for the sake of learning. Such studentssee effort as positive and therefore persist through tough obstacles. Ultimately,students holding an incremental mindset tend to achieve at higher levels than theirpeers holding a fixed mindset.

So why do students adopt one type of mindset over another? Some suggest thatteachers mindsets and methods of evaluation influence the type of mindset theirstudents develop (Good et al. 2012; Rattan et al. 2012). Others suggest that the typeof feedback a teacher provides also influences mindsets (for a review, see Dweck andMaster 2009). For example, describing the outcomes and great accomplishments ofindividuals without emphasizing their relentless commitment can promote a fixedmindset. However, when teachers emphasize the importance of strategies and persis-tence, students are more inclined to view their abilities as augmentable, which can leadto an incremental mindset.

Interest in and Enjoyment of Mathematics Learning

A substantial body of literature has shown that interest in academic study declinesmeasurably, particularly as students enter their adolescent years (which in theUnited States is during grades six to twelve). Many interventions, especially inmathematics, have been crafted to address this decline in academic interest. Tounderstand the ways researchers can design interventions that target academicinterest, we invoke Hidi and Renningers (2006) four-phase model of interestdevelopment. Interests come, they claim, in two types: situational and individual.First, interests start out as situational, which are short-lived and often requiresubstantial external support to sustain. Typically, students first experience aretriggered situational interest in something which is surprising, personally relevant,or especially enjoyable. It sparks a temporary interest.

The second phase occurs when this trigger translates into a situational interest that ismaintained, where students interests are sustained through personally meaningful tasksand/or personal involvement. If such interest is maintained and developed, it can turninto an individual interest, which are more well developed and longer lasting. Anemerging individual interest is typically characterized by stored knowledge, value, andpositive affect, which, if sustained over time, can then develop into what is termed awell-developed individual interest, one in which students possess robust stored knowl-edge and value for the subject. Students at this stage are able to re-engage with tasksrelated to the specific subject topic or almost entirely on their own volition.

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Leveraging Technology as a Motivational Tool

The research literature includes examples of technology interventions that have suc-cessfully targeted self-efficacy, implicit theories of ability, and interest and enjoyment.Digital resources can support gains in self-efficacy when learning about science,particularly through providing mastery experiences for students, by allowing them tosee the fruits of their own labor. For instance, Ketelhut et al. (2010) found that studentswith low initial self-efficacy who participated in a multi-user virtual environment(MUVE) called River City rated themselves more self-efficacious at inquiring scientif-ically. By the end of the intervention, low initial self-efficacy students behavedsimilarly to those with high initial self-efficacy, gathering data in the virtual world asthoroughly as students with high self-efficacy.

Similarly, Liu et al. (2006) showed that students self-efficacy for learning scienceincreased after participation in a computer-enhanced, problem-based learning (PBL)environment called Alien Rescue. The study found that student gains in self-efficacycame from opportunities to see themselves succeed without assistance, rather thanhaving a teacher tell them how to succeed. These two studies illustrate how technologycan support student self-efficacy by providing relevant mastery experiences thestrongest hypothesized source of self-efficacy.

Similarly, some evidence exists demonstrating the effect of digital resourcestargeting our second motivational construct: students implicit theories of ability.Specifically, Dweck and colleagues have developed Brainology,1 a web-based seriesof learning modules designed to teach students about the incremental mindset (termedthe growth mindset). Dweck and colleagues have reported promising results usingtheir paper-based growth mindset intervention (see Blackwell et al. 2007). These resultsshowed that students in a control group, who were not taught a growth mindset,displayed a continuing downward trajectory in grades and motivation, whereas theexperimental group displayed an upward one. Despite these promising findings,however, the web-based material, which is modeled on the paper-based version, lacksrigorous large-scale efficacy studies to support its claims of effectiveness.

Third, scholars have been able to show that digital resources can be deployed to recruitstudents interest and enjoyment. For example,Quest Atlantis (a three-dimensional virtualworld) has been shown to make particular learning goals interesting by placing themwithin a fun and meaningful context in which students...